A Hybrid Batch Mode Fault Tolerance Strategy in Desktop Grids

A Hybrid Batch Mode Fault Tolerance Strategy in Desktop Grids

Geeta Rani (Chitkara University, India) and Jyoti Bansal (Baba Farid College of Enggineering & Technology, Bhatinda, India)
Copyright: © 2020 |Pages: 15
DOI: 10.4018/IJNCR.2020040103

Abstract

Desktop grids make use of unused resources of personal computers provided by volunteers to work as a huge processor and make them available to users that need them. The rate of heterogeneity, volatility, and unreliability is higher in case of a desktop grid in comparison to conventional systems. Therefore, the application of fault tolerance strategies becomes an inevitable requirement. In this article, a hybrid fault tolerance strategy is proposed which works in three phases. First, two phases deal with the task and resource scheduling in which appropriate scheduling decisions are taken in order to select the most suitable resource for a task. Even if any failure occurs, it is then recovered in the third phase by using rescheduling and checkpointing. The proposed strategy is compared against existing hybrid fault tolerance scheduling strategies and ensures a 100% success rate and processor utilization and outperforms by a factor of 3.5%, 0.4%, and 0.1% when turnaround time, throughput, and makespan, respectively, are taken into account
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2. Review Of Literature

Desktop Grid resources are volatile, dynamic and diverse in nature. Faults are expected to occur due to the unpredictable environment of grid (Zheng & Veeravalli 2009; Lee et al., 2009; Sathya & Babu, 2010). Various fault handling strategies are designed to handle failures without affecting the quality of service (QoS). Fault handling strategies can be pro-active or post-active based upon whether faults are handled before or after job execution

Proactive fault tolerance strategies handle the failures before the execution of the task and scheduled with the expectation that task will never fail. Proactive strategies need information concerning i.e. grid tasks, resources, fault types, fault occurrence etc. for effective scheduling. Based on the available information, the decisions to handle the probable failures are taken.

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